
CIFAR10 [1]} contains 60,000 RGB images of size \(32\times 32\)  from 10 classes, in which 50,000 images are for training and 10,000 images are for test.

CIFAR100 [1]} also contains 60,000 RGB images of size \(32\times 32\) , except that it contains 100 classes with 500 training images and 100 test images per class.

SVHN [3]} is a street view house number dataset containing 73,257 training images and 26,032 test images classified into 10 classes representing digits. Each image may contain multiple real-world house number digits, and the task is to classify the center-most digit.

